It's no secret CIOs struggle to keep up with unyielding streams of both structured and unstructured data.

However, the ability to mine this data and unlock strategic insights is critical to the success of every business. And while their C-level peers are well-versed in interpreting data into actionable insights, CIOs are tasked with effectively balancing business growth, sales, marketing, and security priorities with evolving technical challenges.

So, what is the right level of interdependence between the CIO and his/her counterparts in the C-suite?

Here are a few tips on how CIOs can navigate the pressure points and best collaborate with security and other leaders in their organizations when it comes to the enterprise's overall security strategy and data.

1. Big Data

Marketing leads, sales metrics, financial reports, threat intelligence, security alerts, application performance metrics and infrastructure logs — the list of data sources in the enterprise is seemingly endless.

How does a CIO get and stay on top of all of these silos of information, providing targeted data sources and solutions to peers such as the CMO and CISO in addition to maintaining a highly available, resilient infrastructure?

It's important to first differentiate between providing systems of record for data and consuming data from systems of record.

Teams under the respective CxO should be solely focused on the latter, where the CIO organization should be tasked with delivering the technical solutions that provide easy access to the data stored within each distinct system of record.

2. Collaborative assessment

The first step is to determine what data sources are important to the CISO and their respective teams and document that inventory, including the priority levels. Even the best technical solution will fail if you're not providing relevant data sources; that is the quickest way to having "shadow IT" proliferate throughout the company.

It is also important to note that this data inventory assessment exercise is never done, there will be new data sources emerging and existing ones may be found to not provide the value that they once did. Data sources must be evaluated regularly to ensure both business impact and reduce potential security exposure.

3. Data locality

Location, Location, Location. With vast amounts of data comes the requirement to store it in a location that is both closest to the consumer and the most resource/cost effective long term.

Big Data has a substantial amount of "gravity" and there is a significant penalty incurred if you need to move it to another location, either on public cloud storage or in private infrastructure.

Another factor that needs to be considered when choosing a storage location is if the data has any associated regulatory requirements such as PII for personal identification data and the forthcoming GDPR compliance law in the EU.

4. Data collation

In addition to storing data in the correct location, it has to be properly organized so that it can be easily discovered and consumed by the security teams.

This part of the strategy needs to be continuous, as it's easy for data sources to become unorganized and/or "stale." This is best addressed by, once again, collaborating with the various groups accessing and analyzing the data.

It's extremely easy for data ponds and lakes to turn into murky swamps, so being proactive is paramount in preventing that from occurring.